Structural analysis of endothelial projections from mesenteric arteries
Bibliographic record
Abstract
OBJECTIVE: Endothelial and smooth muscle cells must communicate with one another to regulate arterial diameter. A key structure driving heterocellular communication is the endothelial projection, a thin extension that crosses the internal elastic lamina (IEL) making contact with smooth muscle. This study sought to define the precise structural composition of endothelial projections in the mesenteric circulation. METHODS: Third- and fourth-order mesenteric arteries from hamster were prepared for electron microscopy. Electron tomographic approaches were used to generate 3-D compositional models of endothelial projections. RESULTS: Endothelial projections were categorized based upon their proximity to smooth muscle or how many projections projected through an IEL hole. Irrespective of the initial categorization, endothelial projections were largely devoid of organelles except for sparse membranous structures observed near the tip, close to potential smooth muscle contact sites. Unexpectedly, it was the base of projections which were rich with organelles including the endoplasmic reticulum, ribosomes, vesicles, caveolae, and mitochondria. CONCLUSIONS: Electron tomographic techniques suggest that the base of endothelial projections is likely a dynamic site for signal regulation and contractile control. As projections are largely devoid of membranous organelles, their principal function appears to ensure electrical contact between the two cell layers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".